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我試圖用scikit學會做線性迴歸與幾個輸出Scikit學習線性迴歸與幾個輸出
碼（隨機數據爲例）：
from sklearn import datasets, linear_model
import numpy as np
X = np.random.rand(300,10)
y = np.random.rand(300,9)
reg_model = linear_model.LinearRegression()
reg_model.fit(X,y)
我得到collowing錯誤：
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
/Users/sorensonderby/Documents/workspaces/workspace/Chemoinformatics_proect/notebooks/<ipython-input-116-e235c7159573> in <module>()
5 y = np.random.rand(300,9)
6 reg_model = linear_model.LinearRegression()
----> 7 reg_model.fit(X,y)
8
/Library/Python/2.7/site-packages/scikit_learn-0.10-py2.7-macosx-10.7-intel.egg/sklearn/linear_model/base.pyc in fit(self, X, y)
178 linalg.lstsq(X, y)
179
--> 180 self._set_intercept(X_mean, y_mean, X_std)
181 return self
182
/Library/Python/2.7/site-packages/scikit_learn-0.10-py2.7-macosx-10.7-intel.egg/sklearn/linear_model/base.pyc in _set_intercept(self, X_mean, y_mean, X_std)
106 """
107 if self.fit_intercept:
--> 108 self.coef_ = self.coef_/X_std
109 self.intercept_ = y_mean - np.dot(X_mean, self.coef_.T)
110 else:
ValueError: operands could not be broadcast together with shapes (10,9) (10)
我讀的擬合方法的API，它說，X應該是n樣本X n_features和y應該是n樣本X n_targets。 Link to fit method
我在做什麼錯？